Create an understanding of FPL data and create a python notebook to engineer it into Azure

[pratik-IDWT]

Useful Articles

https://medium.com/analytics-vidhya/getting-started-with-fantasy-premier-league-data-56d3b9be8c32

Steps to be taken

1. Understand Data available in API - Pick any Data API to test
2. Create a data pipeline to store data in Azure SQL Database
3. Once known, design a data model and key metrics
4. Build data pipelines and monitor
5. Create a AI use case to improve my FPL team

[pratik-IDWT]

Update

Key activities identified, each to have their own ticket and summary to be written

[pratik-IDWT]

Notebooks to Refer too

In trying to make my own FPL data loading and transforming, A repo is available that I can refer too that explains it here - https://github.com/James-Leslie/fpl-data/tree/main/notebooks

[pratik-IDWT]

Notebook Prototype

A notebook prototype has been drafted here - https://github.com/In-Data-We-Trust/IDWT-All-Things-SQL-And-Python-And-Code/blob/main/Python_Reference/FPL_Prototype.ipynb

I will continue to enhance it to have a ful use case for pulling in data for FPL, which can then be used for an AI prototype

[pratik-IDWT]

Quick note of a link

I need to create a DDL from a pandas DF, will reference this later this week - https://medium.com/@mgangrade7/create-sql-table-using-python-for-loading-data-from-pandas-dataframe-985281dde307

[pratik-IDWT]

Update to Close this Ticket

What have I done?

I have written a python notebook, which when run from start to finish, write the key FPL data into my Azure DB.

The notebook is stored here - https://github.com/In-Data-We-Trust/IDWT-All-Things-SQL-And-Python-And-Code/blob/main/Python_Reference/FPL_Prototype.ipynb

What's Next?

1. Make a simple query that brings together the data for these tables

2. Run the query and store into a modelled table or tables
3. Generate some trending analytics

What's the AI use case?

This need some thought but I can do one of a few things:

• Create a public facing web based tool, that lets you talk to the dataset and retrieve approved analytics through training and retrieval-augmented generation (RAG) principles
• Let AI analyse the data and show me trends